Medical Image Analysis
Volume 15, Issue 1 , Pages 22-34, February 2011

Segmentation and reconstruction of vascular structures for 3D real-time simulation

  • Xunlei Wu

      Affiliations

    • Renaissance Computing Inst., Univ of North Carolina at Chapel Hill, USA
    • The SIM Group and Department of Imaging, Mass. General Hospital, Cambridge, USA
  • ,
  • Vincent Luboz

      Affiliations

    • Dept. of Biosurgery and Surgical Technology, Imperial College London, UK
    • The SIM Group and Department of Imaging, Mass. General Hospital, Cambridge, USA
    • Corresponding Author InformationCorresponding author at: Dept. of Biosurgery and Surgical Technology, Imperial College London, UK. Tel.: +44 (0) 207 886 6379; fax: +44 (0) 207 886 6309.
    web address
  • ,
  • Karl Krissian

      Affiliations

    • Dept de Informática y Sistemas, Univ. Las Palmas de Gran Canaria, Spain
  • ,
  • Stephane Cotin

      Affiliations

    • ALCOVE Team, INRIA Lille – North Europe, France
    • The SIM Group and Department of Imaging, Mass. General Hospital, Cambridge, USA
  • ,
  • Steve Dawson

      Affiliations

    • The SIM Group and Department of Imaging, Mass. General Hospital, Cambridge, USA

Received 22 March 2009; received in revised form 7 June 2010; accepted 21 June 2010. published online 02 July 2010.

Abstract 

We propose a technique to obtain accurate and smooth surfaces of patient specific vascular structures, using two steps: segmentation and reconstruction. The first step provides accurate and smooth centerlines of the vessels, together with cross section orientations and cross section fitting. The initial centerlines are obtained from a homotopic thinning of the vessels segmented using a level set method. In addition to circle fitting, an iterative scheme fitting ellipses to the cross sections and correcting the centerline positions is proposed, leading to a strong improvement of the cross section orientations and of the location of the centerlines. The second step consists of reconstructing the surface based on this data, by generating a set of topologically preserved quadrilateral patches of branching tubular structures. It improves Felkel’s meshing method (Felkel et al., 2004) by: allowing a vessel to have multiple parents and children, reducing undersampling artifacts, and adapting the cross section distribution. Experiments, on phantom and real datasets, show that the proposed technique reaches a good balance in terms of smoothness, number of triangles, and distance error. This technique can be applied in interventional radiology simulations, virtual endoscopy and in reconstruction of smooth and accurate three-dimensional models for use in simulation.

Keywords: Brain, Heart, Skeletonization, Segmentation and reconstruction, Vascular network

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 The work presented in this paper is solely the result of the authors research and no opinion or endowment by the Department of Defense should be inferred.

PII: S1361-8415(10)00069-1

doi:10.1016/j.media.2010.06.006

Medical Image Analysis
Volume 15, Issue 1 , Pages 22-34, February 2011